Recently introduced 3D Time-of-Flight (ToF) cameras have shown a huge potential for mobile robotic applications, proposing a smart and fast technology that outputs 3D point clouds, lacking however in measurement precision and robustness. One advantage of their usage is the complete removal of the typical stereo vision pipeline, but they are subject to noise depending on the density and reflectivity of the materials hit by their illuminators. With the development of this low-cost sensing hardware, 3D perception gathers more and more importance in robotics as well as in many other fields, and object registration arouses everyday more attention. Registration is a transformation estimation problem between two input point clouds, seeking the transformation that best aligns the source to the target.